A central goal of functional genomics is to identify genes or other genetic elements (e.g., operons) that are associated with or result in particular phenotypic traits. With the completion of the Human Genome Project and related efforts in other species, a great deal of raw genomic sequence information has become available. However, in many cases the location of expression units (genes) within this vast amount of sequence information remains to be determined. Even where genes or other genetic elements have been identified, their function is frequently unknown.
Both positive and negative phenotypic traits may be conferred by the interplay between genetic elements and environmental conditions. Positive traits may include such characteristics as growth rate, yield, disease resistance, resistance to environmental stresses such as temperature or drought, ability to grow on minimal media, etc. Examples of negative traits might include a predisposition or susceptibility to develop genetically based diseases, such as cancer, heart disease, diabetes and other conditions. In either case, it would be advantageous for the scientist, clinician or other researcher to be able to identify those genetic elements that influence or result in particular traits. Although identification of trait associated genetic elements is of significance in eukaryotes, it is also important in prokaryotes for applications such as biopharmaceutical production, bioremediation, development of chemical tolerance, identification and/or neutralization of antibiotic resistance genes, etc.
A variety of approaches have been attempted to identify trait conferring genetic elements. One approach has been to examine gene expression profiles in different tissues (e.g., diseased vs. normal), at different developmental stages, in response to various environmental factors, or across different physiological classes (e.g., DeRisi et al., 1997 Science 278, 680-685; Roberts et al., 2000, Science 287, 873-880; Schena et al., 1995, Science 270, 467-470). Other approaches have included transformation, gene deletion and complementation studies (see, e.g., Sambrook et al., 1989, Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Laboratory Press, Plainview, N.Y.). Various techniques have utilized deletion libraries marked with identifiable sequences to replace individual genes, analyzed on oligonucleotides or PCR-based spotted microarrays (Winzeler et al., 1999, Science 285, 901-906; Shoemaker et al., 1996, Nat. Genet. 14, 450-456; Badarinarayana et al., 2001, Nat. Biotechnol. 19, 1060-1064). Other alternatives have included overexpression libraries studied by standard plating methodologies (Cho et al., 1998, Proc. Natl. Acad. Sci. USA 95, 3752-3757). More recently, a genome-wide screening technique using hybridization to DNA microarrays has been attempted (Gill et al., 2002, Proc. Natl. Acad. Sci. USA 99:7033-38). Even though DNA microarrays have been used to probe extra-chromosomally based genomic libraries in E. coli, such approaches have been severely limited by a requirement for substantial subcloning of regions of selected chromosomal DNA and, as a consequence, they do not provide quantitative data concerning the effect of overexpression or increased copy on a relevant phenotype.
Despite these efforts, the identification of genes conferring particular traits of interest has lagged significantly behind genome sequencing efforts. One problem with such approaches has been in the identification of a trait conferring gene within inserts containing multiple genes or genetic elements. Another difficulty has been in the detection of trait causing genetic elements against a considerable background of genetic “noise,” such as random or unexplained differences in gene expression levels or allele frequencies that are unrelated to the trait of interest. A lack of reproducibility in trait associated gene mapping studies has generally resulted. An unresolved need exists for reliable and reproducible methods and compositions capable of identifying trait associated and/or trait conferring genetic elements.